Diffusion-weighted imaging of the liver is prone to the cardiac pulsation artifact, which can lead to reduced lesion visibility. We addressed this problem with a two-fold approach. First, flow-compensated diffusion weightings were used, which are known to reduce this artifact. Using a dataset of 40 patients suffering from focal liver lesions, we addressed the remaining signal voids with different postprocessing techniques, namely weighted averaging, the p-mean approach, and an outlier exclusion algorithm. The algorithms substantially increased the lesion visibility and further reduced the pulsation artifact. An evaluation of CNR and calculation time showed that weighted averaging was suited best.
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